­perfusion ­measurement may be considered as “hypoxia imaging” (Tóth et al. 2013). Tumor hypoxia is considered as an important motor of malignant transformation and, therefore, increases the tumor’s aggressiveness. It also causes resistance of the tumor to chemotherapy and radiation mediated by the activation of HIF-1α and carbonic anhydrase IX and XII (Harguindey et al. 2009). The indirect measurement of hypoxia by T2′ quantification might provide insight into the pathophysiology of brain tumors and into the effects of therapy (Hattingen et al. 2013; Hoskin et al. 2007). Saitta et al. could show that high-grade tumors revealed lower T2′ values, suggesting a higher degree of hypoxia in these fast growing and proliferating tumors (Saitta et al. 2011). However, it is not possible to differentiate deoxyHb from other microscopic sources of susceptibility effects like tumor microbleeds. This might result in confounding results in glioblastomas, since microbleeds are a very typical characteristic of this type of brain tumor. It has turned out that the detection of microbleeds in high-grade gliomas is very helpful for discriminating them from other space-occupying pathologies such as demyelinating lesions, lymphomas, and metastases (see below).

Since microbleeds are best detected with high-resolution susceptibility-weighted imaging (SWI), this method plays an important role in tumor diagnosis. Since field inhomogeneities and thus susceptibility effects increase with the field strength, this relatively new MR technique benefits from higher field strengths which become increasingly available in the clinic. In SWI, filtered phase and magnitude information are combined to create a new susceptibility-weighted image contrast (Haacke et al. 2004). SWI visualizes normal or pathological venous structures and microbleeds that are not visible on conventional MR images. Pronounced intratumoral susceptibility signals (ITSS) are found in almost all glioblastomas but not in CNS lymphomas, demyelinating diseases, and low-grade gliomas (Mittal et al. 2009; Park et al. 2010; Peters et al. 2012). In most cases, microbleeds in metastases are less pronounced compared to microbleeds in glioblastomas (Park et al. 2010). Furthermore, intralesional venous structures differ considerably between different space-occupying brain lesions. The perivenous inflammation in multiple sclerosis (MS) lesions shows a typical SWI pattern revealing normal venous structures which are the lead structures for the MS plaques (Mittal et al. 2009). In contrast, high-grade gliomas not only show prominent microbleeds, but also a distorted and irregular neovasculature (Kim et al. 2009; Mittal et al. 2009).

4\ Longitudinal Relaxation Time T1

Several studies showed a positive correlation between the brain water content and the T1 relaxation time (MacDonald et al. 1986; Fatouros et al. 1991). The positive correlation of the mean diffusivity of water (Bastin 2002) and the T1 relaxation time and a significant T1 reduction under antiedematous therapy support the hypothesis that the T1 relaxation time reflects the tissue

water content (Andersen et al. 1993). Longer T1 values were found in enhancing lesions of MS patients compared to nonenhancing lesions, indicating a disruption of the BBB and hence a higher water content in the adjacent brain tissue prolonging T1 (Jurcoane et al. 2013). Human and animal studies showed prolonged T1 relaxation times in glioblastomas and their peritumoral edema compared to normal brain tissue (Englund et al. 1986; Hoehn-Berlage and Bockhorst 1994) and other tumors such as meningiomas and schwannomas. In contrast, necrotic tumor tissue might display a shortened T1 relaxation time which might be due to the presence of methemoglobin or mineralization (Bähr et al. 2011; Boyko et al. 1992). It should be mentioned that T1 shortening might also be a prognostic marker for the survival time of patients with recurrent glioblastomas under antiangiogenic therapy (Bähr et al. 2011, 2014).

The presence of contrast agents containing gadolinium (Gd) or manganese (Mn) shortens the T1 relaxation time considerably. Furthermore, co-registered maps of the longitudinal relaxation time before (qT1) and after application of a contrast agent (qT1+CA) allow for voxel-wise subtraction of (qT1+CA) from qT1 (Fig. 3). This approach enables the quantification of an even subtle contrast agent enhancement independent of visual detectability (Jurcoane et al. 2013), yielding sensitive quantification of the BBB damage (Jurcoane et al. 2013).

However, further studies are required to answer the question if T1 mapping, alone or in combination with T2 mapping, histograms of T1 and T2 relaxation times in the tumor tissue and edema, and more sophisticated three-dimensional tumor segmentation methods are valuable tools to delineate tumor tissue and edema and if these techniques are of help in differential diagnosis and therapy monitoring.

5\ Chemical Exchange Saturation

Transfer (CEST)

The CEST method is based on the magnetic transfer effects of specific protons in metabolites (and exogenous contrast agents) that are in chemical exchange with the solvent. The method for detecting CEST contrast is similar to the magnetization transfer (MT) contrast, i.e., the intensity change of the water signal is monitored­ in the presence of off-resonance saturation. A CEST effect is observed when the off-resonance frequency matches the MR frequency of a metabolite proton which is exchanging with the water protons at an appropriate rate. By varying the frequency, power, and timing of the saturation pulses, CEST contrast can be tuned to signals from endogenous mobile proteins and peptides (amide proton transfer, APT) (Zhou et al. 2003a, b) to amino protons of glutamate (gluCEST) (Cai et al. 2012) or to hydroxyl protons like those from glucose (glucoCEST) (Chan et al. 2012; Nasrallah et al. 2013). Since the basic principle of the contrast relies on proton exchange with the solvent and therefore depends on the concentration of solvent protons, the method allows to measure tissue pH (Zhou et al. 2003b).

Fig. 4  Chemical exchange saturation transfer (CEST) method (With permission from van Zijl and Yadav (2011)). Further explanation is given in the text (Method)

a

b

c

d

6\ Cest Method

There are several articles which review the basic principles of CEST (Sherry and Woods 2008; van Zijl and Yadav 2011; van Zijl et al. 2003). Briefly, the method exploits the magnetization transfer (MT) effect which is well known from MT-MRI (Tofts 2003). In MTR contrast is generated by selectively irradiating off-resonance from the water signal, modifying the magnetization of macromolecules which are in contact with the water. By several mechanisms, this magnetization is transferred to the water protons detected with conventional MRI, causing a partial saturation and consequently a signal modification. The efficiency of the magnetization transfer is typically changed in several pathological

situations providing a surrogate marker for affected tissues (Tofts 2003). Like in MTR, CEST-MRI monitors the effect (signal reduction) of an off-resonance irradiation on the water signal; however, the target molecules for irradiation are rather small (amino acids, peptides, glucose, exogenous agents with specific properties) and have a well-defined typical resonance frequency which is known from MR spectroscopy (see Chap. MR Spectroscopic Imaging). Some of the protons in these molecules are exchanged with the solvent (water). Selective saturation of these protons will transfer their magnetization to the MRI-­detectable water signal, enabling the quantification of the exchange partner by measuring the signal changes of the solvent.

The effect is shown in Fig. 4.

The upper row (a) shows a scheme of the exchange ­mechanism, while the left part of row b depicts the MR spectrum of a sample with an aqueous solution containing a solute with amide protons (e.g., from polypeptides). On the left of the huge water signal at 4.75 ppm (S0), a weak signal at 8.25 ppm from exchangeable amide protons is visible. Saturation of these protons by RF irradiation at 8.25 ppm not only removes this signal but also causes a significant

decrease of the water signal (Ssat, right). The decrease of Ssat can be detected as contrast in MRI. Performing a series of

measurements with different offset frequencies for saturation provides a so-­called Z-spectrum or CEST spectrum which is shown in row c. In the CEST spectrum, the normalized water signal (Ssat/So) in the presence of saturation is plotted versus the frequency difference between the water and the offset irradiation frequency ( ω). Obviously, irradiation at the water signal frequency will saturate the water protons causing a minimal Ssat (direct saturation, DS). In addition to DS, there is also the MT effect which reduces the water signal intensity in the presence of off-resonance irradiation. In a first approximation, DS and MT can be considered as independent of the sign of ω causing a symmetric Z-spectrum around the water frequency. In contrast, saturation of the water protons via exchange with saturated amide protons only appears when the saturation frequency matches the position of the amide protons (3.5 ppm to the left of water), resulting in an additional dip in Ssat/So at this frequency.

Defining the term MTRasym

which determines the asymmetry of the MTR effect correct-

ing for DS and symmetric MT provides the MTRasym spectrum which is shown in row d. Chemical exchange is evident

as signal at the position of the exchanging amide protons. This signal reflects a change in water proton intensity and can be detected with methods known from MT-MRI. Compared to conventional MRSI, the methods have a huge potential for signal enhancement which increases with the exchange rate

kexchange but is counteracted by the T1 relaxation of tissue water. Also, the efficiency of saturation of solute protons by contin-

uous RF irradiation depends on the ratio ω/kexchange. Ideally ω/kexchange > > 1 (slow exchange regime) is required to allow sufficient saturation with reasonable RF power (van Zijl and

Yadav 2011), a condition which, at clinical field strength of 3 T, is only fulfilled for amide protons. Consequently, most applications on human brain tumors are focused on mobile proteins and polypeptides, measuring either their concentrations or tumor environmental changes which can modify the exchange rate (Zhou et al. 2003a; Togao et al. 2014). Amino and hydroxyl protons usually fall in the slow to medium

exchange regime ( ω/kexchange ~ 1), but it has been shown that glucose and glycogen can be detected with CEST in animal

models at high magnetic field strengths (>9 T, (Chan et al. 2012; Nasrallah et al. 2013; van Zijl et al. 2007)). Recently it was proposed that spin-locking (SL) techniques are more suited for the intermediate exchange regime (Lin et al. 2011; Jin et al. 2012) and pilot studies could detect myoinositol (Haris et al. 2011) and glutamate (Cai et al. 2012) using this method. However, no applications in oncology are published yet; thus, a description of these methods would be beyond the scope of this short overview.

In summary, for a metabolite with protons that are in exchange with the water, CEST provides a contrast which is specific to their concentration (like parameter images in MRSI) but with a signal intensity comparable to MT contrast. The following metabolites were detected via magnetization transfer mediated by chemical exchange of protons with the water:

•Amide protons in peptide bonds (endogenous mobile proteins and peptides) (APT-CEST)

•Glutamate (gluCEST)

•Glucose, glycogen, and myoinositol (glucoCEST)

Also, exogenous CEST agents have been introduced

(Ward et al. 2000), and their function as pH marker has been tested as proof of principle (Ward and Balaban 2000)

While the concept of CEST imaging is very intriguing, there are various pitfalls which might render the method as too complicated and up to now not very robust for routine clinical use:

•Like MT-MRS, the method requires a rather quantitative approach to correct for many competing mechanisms which can cause a decrease in signal intensity.

•Many parameters are affecting the exchange rate. Thus, the CEST-induced contrast might be ambiguous.

•Long measurement time and SAR problems.

7\ CEST Imaging in Brain Tumors

There is an increasing number of publications dealing with CEST in brain tumors. APT was introduced by Zhou et al. (2003b). First in vivo data from brain tumors were published by the same group 3 years later (Jones et al. 2006). A 3–4 % increased APT signal was found in brain tumors compared to peritumoral brain tissue or in animal models comparing glioma with radiation necrosis in rats (Zhou et al. 2008, 2011). Amide protons in the cytoplasm are thought to be the major source of the APT signal intensity. As known from FET-PET (Chap. Advanced MR Methods in Differential Diagnosis of Brain Tumors), glial brain tumors have an increased amino acid uptake compared to normal brain. Furthermore, an increased APT signal intensity was also found in necrotic high-grade gliomas, indicating that highly concentrated mobile proteins and peptides in the microcystic extracellular space might also increase APT signal intensity in tumors. In contrast to PET, the APT measures the endogenous content of amide protons without requiring external contrast agents.

Apart from the costs, this might be an advantage ­concerning repetitive follow-up examinations especially in young tumor patients. Recently, a study of thirty-six patients showed that APT signal intensity did not only differentiate between gliomas WHO grade II and IV, but also between gliomas WHO grade II and III and between gliomas WHO grade III and IV (Togaoetal.2014).Thus,APTseemstobeapromisingmethod for tumor grading and for depicting tumor heterogeneity. Referring to the experiences in FET-PET (Chap. Advanced MR Methods in Differential Diagnosis of Brain Tumors), APT might even be a promising method to differentiate between therapy-induced changes and tumor progression in brain tumor patients. As mentioned above, the exchange rate depends on the pH; thus, the tumor pH (Chap. MR Spectroscopic Imaging) also affects the APT signal intensity. On the other hand, pH can be measured with CEST, providing another parameter which could be exploited in tumor diagnosis. This requires to eliminate ambiguous influences between the pH and amide proton content, e.g., by combination with an independent pH measurement using phosphorus MR spectroscopy (Chap. MR Imaging of Brain Tumors).

Glycolysis, either anaerobic or aerobic, is enhanced in high-grade brain tumors, and an overexpression of glucose transporter (GLUT) proteins has been found in glioblastoma. An increased uptake of glucose in PET is a typical finding in malignant brain tumors. First results indicate that glucose concentrations can be detected by CEST via the hydroxyl protons (glucoCEST) (Nasrallah et al. 2013). Significant enhancement of the glucoCEST signal has been found upon systemic glucose infusion in an experimental study with breast cancer cells (Chan et al. 2012). However, to our knowledge, this method has not been evaluated for in vivo gliomas. It might be an interesting tool to evaluate alternative glioma therapies such as the low-carbohydrate, ketogenic diet (Rieger et al. 2014).

Although not yet applied in oncological systems, another variation of CEST with great potential is the depiction of chemical exchange saturation transfer effect between the amine group of glutamate and bulk water, also named gluCEST (Cai et al. 2012). Here, the CEST effect depends on the pH and glutamate concentration. Glutamate is released from glioma cells, possibly as by-product of GSH synthesis, an antioxidant which enhances the resistance to oxidative stress (Sontheimer 2008). In addition, glutamate is an important anaplerotic substrate which delivers α-ketoglutarate to the citrate cycle. It substitutes the intermediates of the citrate cycle which are used for protein biosynthesis in proliferating tumor cells. Glutamate can be transformed to glutamine through the glutamate-glutamine cycle of reactive astrocytes. Glutamine is a major metabolic fuel for both brain tumor cells and tumor-associated macrophages, which may create a microenvironment that facilitates aggressive growth of tumor cells. Using MR spectroscopy, increasing gluta-

mate concentrations were found in brain tumors (Kimura et al. 2007; Rijpkema et al. 2003). However, a reliable quantification of glutamate concentrations in tumor spectra is ­frequently ­hampered by the modulated baseline due to higher ­concentrations of lipids and macromolecules. Therefore, future investigations have to show whether gluCEST can provide reliable values for glutamate in tumors.

The methods based on chemical exchange contrast have a high potential to provide essential information on tumor biology, however, apart from CEST with amide protons (APT), these methods are still experimental. APT can be performed on clinical scanners and has been applied to human brain tumors providing promising results for diagnostic purposes. Since the CEST mechanism depends on metabolite concentration and pH, the reliability and robustness of the results have to be evaluated in studies with larger patient cohorts at different medical centers. In contrast, quantitative relaxometry and related methods are well suitable for standardized tumor diagnosis and monitoring, but their biological ­significance has to be validated in the future.

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